3G and 4G paging success rate based mobile network anomaly detection using supervised and unsupervised learning

3G and 4G paging success rate based mobile network anomaly detection using supervised and unsupervised learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2022.

Podrobná bibliografie
Hlavní autor:	Ahasan, Md Rakibul
Další autoři:	Alam, Md. Golam Robiul
Médium:	Diplomová práce
Jazyk:	English
Vydáno:	Brac University 2022
Témata:	Anomaly detection Supervised learning KPI Mobile Networks SMOTE Unsupervised learning K-Means DBSCAN HDBSCAN Autoencoder Algorithms Computer network architectures
On-line přístup:	http://hdl.handle.net/10361/17164

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